A new global scale river's slope dataset

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dc.contributor Davis, Lisa
dc.contributor Zhang, Yong
dc.contributor.advisor Cohen, Sagy
dc.contributor.author Wan, Tong
dc.date.accessioned 2017-03-01T17:57:58Z
dc.date.available 2017-03-01T17:57:58Z
dc.date.issued 2016
dc.identifier.other u0015_0000001_0002453
dc.identifier.other Wan_alatus_0004M_12835
dc.identifier.uri https://ir.ua.edu/handle/123456789/2744
dc.description Electronic Thesis or Dissertation
dc.description.abstract River’s slope (bed and flow) is a key parameter in fluvial hydrology, hydraulics and geomorphology. It affects many important fluvial variables such as flow velocity and sediment transport, especially bedload. Limitation in river’s slope data confined fluvial modeling, particularly at large scales. Traditional slope calculation algorithms cannot accurately predict river’s slopes as these are based on cell-by-cell calculation, which is only suitable for hillslopes and steep mountainous streams. This paper presents a new algorithm for calculating global river’s slope and a procedure to upscale it for relatively course resolution global hydrological modeling. The algorithm is based on a simple principle of calculating slope from elevation depression over the length of a river segment. The algorithm automates this calculation for global rivers. In this paper, the HydroSHEDS 15 arc-sec Digital Elevation Model is used for calculating global river network and retrieving the elevation values. A sensitivity analysis is conducted in order to examine the effect of maximum river segment length on slope predictions. An analysis of the accuracy of this dataset has been conducted by comparing the new dataset against observed slope data collected from the literature and an independent high-resolution stream network layer for the contiguous United States. The results show that this algorithm is able to accurately calculate global river’s slope. Applications of the resulting dataset are proposed.
dc.format.extent 40 p.
dc.format.medium electronic
dc.format.mimetype application/pdf
dc.language English
dc.language.iso en_US
dc.publisher University of Alabama Libraries
dc.relation.ispartof The University of Alabama Electronic Theses and Dissertations
dc.relation.ispartof The University of Alabama Libraries Digital Collections
dc.relation.hasversion born digital
dc.rights All rights reserved by the author unless otherwise indicated.
dc.subject.other Physical geography
dc.subject.other Hydrologic sciences
dc.subject.other Geographic information science and geodesy
dc.title A new global scale river's slope dataset
dc.type thesis
dc.type text
etdms.degree.department University of Alabama. Dept. of Geography
etdms.degree.discipline Geography
etdms.degree.grantor The University of Alabama
etdms.degree.level master's
etdms.degree.name M.S.

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